Abstract: A method for generating a 3D representation of a dynamically changing 3D scene, which includes the steps of: acquiring at least two synchronised video streams (120) from at least two cameras located at different locations and observing the same 3D scene (102); determining camera parameters, which comprise the orientation and zoom setting, for the at least two cameras (103); tracking the movement of objects (310a,b, 312a,b; 330a,b, 331a,b, 332a,b; 410a,b, 411a,b; 430a,b, 431a,b; 420a,b, 421a,b) in the at least two video streams (104); determining the identity of the objects in the at least two video streams (105); determining the 3D position of the objects by combining the information from the at least two video streams (106); wherein the step of tracking (104) the movement of objects in the at least two video streams uses position information derived from the 3D position of the objects in one or more earlier instants in time.

Abstract: Estimating a pose of an articulated 3D object model (4) by a computer is done by •obtaining a sequence of source images (10) and therefrom corresponding source image segments (13) with objects (14) separated from the image background; •matching such a sequence (51) with sequences (52) of reference silhouettes (13?), determining one or more selected sequences of reference silhouettes (13?) forming a best match; •for each of these selected sequences of reference silhouettes (13?), retrieving a reference pose that is associated with one of the reference silhouettes (13?); and •computing an estimate of the pose of the articulated object model (4) from the retrieved reference pose or poses. The result of these steps is an initial pose estimate, which then can be used in further steps, for example, for maintaining local consistency between pose estimates from consecutive frames, and global consistency over a longer sequence of frames.

Abstract: A computer-implemented method for estimating a pose of an articulated object model that is a computer based 3D model of a real world object observed by one or more source cameras, including the steps of obtaining a source image from a video stream; processing the source image to extract a source image segment maintaining, in a database, a set of reference silhouettes, each being associated with an articulated object model and a corresponding reference pose; comparing the source image segment to the reference silhouettes and selecting reference silhouettes by taking into account, for each reference silhouette, a matching error that indicates how closely the reference silhouette matches the source image segment retrieving the corresponding reference poses of the articulated object models; and computing an estimate of the pose of the articulated object model from the reference poses of the selected reference silhouettes.

Abstract: Estimating a pose of an articulated 3D object model (4) by a computer is done by •obtaining a sequence of source images (10) and therefrom corresponding source image segments (13) with objects (14) separated from the image background; •matching such a sequence (51) with sequences (52) of reference silhouettes (13?), determining one or more selected sequences of reference silhouettes (13?) forming a best match; •for each of these selected sequences of reference silhouettes (13?), retrieving a reference pose that is associated with one of the reference silhouettes (13?); and •computing an estimate of the pose of the articulated object model (4) from the retrieved reference pose or poses. The result of these steps is an initial pose estimate, which then can be used in further steps, for example, for maintaining local consistency between pose estimates from consecutive frames, and global consistency over a longer sequence of frames.

Abstract: A method of processing image data includes providing an image sequence such as a video sequence, or a camera transition, identifying a region-of-interest in at least one image of the image sequence, defining a transition region around the region-of-interest and defining a remaining portion of the image to be a default region or background region, applying different image effects to the region-of-interest, the transition region and the background region.

Abstract: What is disclosed is a computer-implemented image-processing system and method for the automatic generation of video sequences that can be associated with a televised event. The methods can include the steps of: Defining a reference keyframe from a reference view from a source image sequence; From one or more keyframes, automatically computing one or more sets of virtual camera parameters; Generating a virtual camera flight path, which is described by a change of virtual camera parameters over time, and which defines a movement of a virtual camera and a corresponding change of a virtual view; and Rendering and storing a virtual video stream defined by the virtual camera flight path.

Abstract: A computer-implemented method for estimating a pose of an articulated object model (4), wherein the articulated object model (4) is a computer based 3D model (1) of a real world object (14) observed by one or more source cameras (9), and wherein the pose of the articulated object model (4) is defined by the spatial location of joints (2) of the articulated object model (4), comprises the steps of obtaining a source image (10) from a video stream; processing the source image (10) to extract a source image segment (13); maintaining, in a database, a set of reference silhouettes, each being associated with an articulated object model (4) and a corresponding reference pose; comparing the source image segment (13) to the reference silhouettes and selecting reference silhouettes by taking into account, for each reference silhouette, a matching error that indicates how closely the reference silhouette matches the source image segment (13) and/or a coherence error that indicates how much the reference pose is con